Factors Associated with Excessive Body Fat in Men and Women: Cross-Sectional Data from Black South Africans Living in a Rural Community and an Urban Township

Abstract

ObjectiveTo determine the factors associated with excessive body fat among black African men and women living in rural and urban communities of South Africa.MethodsThis is a cross-sectional analysis of data from the Prospective Urban and Rural Epidemiology (PURE) study, Cape Town, South Africa conducted in 2009/2010. The study sample included 1220 participants (77.2% women) aged 35–70 years, for whom anthropometric measurements were obtained and risk factors documented through face-to-face interviews using validated international PURE study protocols. Sex-specific logistic regression models were used to evaluate socio-demographic, lifestyle and psychological factors associated with three excessive body fat indicators, namely body mass index (BMI), waist circumference (WC) and body fat percent (BF%).ResultsThe prevalence of excessive body fat based on BF%, WC and BMI cut-offs were 96.0%, 86.1%, and 81.6% for women respectively, and 62.2%, 25.9%, and 36.0% for men respectively. The significant odds of excessive body fat among the currently married compared to unmarried were 4.1 (95% CI: 1.3–12.5) for BF% and 1.9 (95% CI: 1.3–2.9) for BMI among women; and 4.9 (95% CI: 2.6–9.6), 3.2 (95% CI: 1.6–6.4) and 3.6 (95% CI: 1.9–6.8) for BF%, WC and BMI respectively among men. Age ≤50 years (compared to age >50 years) was inversely associated with excessive BF% in men and women, and less-than-a-college education was inversely associated with excessive BMI and WC in men. Tobacco smoking was inversely associated with all three excessive adiposity indicators in women but not in men. Unemployment, depression, and stress did not predict excessive body fat in men or women.ConclusionThe sex-differences in the socio-demographic and lifestyle factors associated with the high levels of excessive body fat in urban and rural women and men should be considered in packaging interventions to reduce obesity in these communities.

Nutritional status and food intake of women residing in rural and urban areas of Lesotho

“…http://orcid.org/0000-0002-3889-0438 amongst urban than rural residents, which resembles findings from South Africa, 19 although others have reported higher prevalence of obesity in rural areas. 20 It is widely recognised that obesity has many negative consequences for health and increases the risk for non-communicable diseases such as cardiovascular diseases and diabetes 21 and the 'metabolic syndrome' .…”

Age and gender differential relationship between employment status and body mass index among middle-aged and elderly adults: a cross-sectional study

“…The relationship between employment status and obesity has been analysed in several studies. [28][29][30][31] The employed showed higher proportion of obesity compared with the unemployed in a Korean adults group. 28 Similarly, the retirement from strenuous job is highly related to BMI.…”

“…29 Conversely, another study presented that employment was less associated with BMI or non-significant. 30 Also obesity increases the probability of unemployment. 31 These complicated relationships could result from the cause of unemployment and the effect of gender.…”

Demographic, socio-economic and behavioural correlates of BMI in middle-aged black men and women from urban Johannesburg, South Africa

“…These associations were independent of behavioural factors including physical activity, smoking and alcohol consumption, and results of the structural equation model confirmed that the association was not mediated by lifestyle. The sex-specific associations highlight the complexity of the association between SES and BMI with studies showing both positive and negative associations in both sexes [10,32,33]. Puoane et al, using data from the South African Demographic and Health Survey, have shown that the association between education and BMI may not be linear in South African women as they showed that women with no formal education and women with tertiary education had a lower BMI than women with some schooling [34].…”

“…The sex difference in obesity prevalence in Africa [6,7] is not observed in high-income countries where obesity is more similar between the sexes [6,8]. Differences in socio-demographic factors and lifestyle behaviours between black South African men and women have been explored in several population-based studies [9,10]; however, whether these factors are interrelated or independent of each other and other potential confounders, and how they are associated with BMI, requires further study.…”